• DocumentCode
    3562364
  • Title

    Accurate detection and complete shape extraction of sand-flies using Gaussian mixture model

  • Author

    Machraoui, Ahmed Nejmedine ; Diouani, Mohamed Fethi ; Ghrab, Jamila ; Sayadi, Mounir

  • Author_Institution
    Lab. of Signal Image & Energy Mastery (SIME), Univ. of Tunis, Tunis, Tunisia
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a method for the accurate detection of the positions of moving phlebotomenae (sand-flies), and the extraction of their complete shape. The proposed method is based on the background subtraction approach, with a statistical background model found using Gaussian mixture model. Furthermore, a method based on the maximization of interclass variance, is used to eliminate wings of the phlebotomenae and then detect accurately its position. Results are further used to study the behaviour of phlebotomenae, and subsequently, improve the traps to fight against many diseases transmitted by these insects, especially leishmaniasis. The experimental results show the efficiency of the proposed algorithm to accurately detect the position and extract the complete shape of moving phlebotomenaes even in case of very blurry ones.
  • Keywords
    Gaussian processes; biology computing; mixture models; object detection; optimisation; shape recognition; Gaussian mixture model; background subtraction approach; interclass variance maximization; phlebotomenae; sand-flies detection; sand-flies shape extraction; statistical background model; Conferences; Diseases; Hidden Markov models; Insects; Shape; Statistics; Tracking; EM algorithm; Gaussian Mixture Model; Motion detection; Video tracking; background subtraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, Applications and Systems Conference (IPAS), 2014 First International
  • Print_ISBN
    978-1-4799-7068-1
  • Type

    conf

  • DOI
    10.1109/IPAS.2014.7043277
  • Filename
    7043277